Estimation tools for reducing the impact of sampling and nonresponse errors in dual‐frame RDD telephone surveys
We discuss alternative estimators of the population total given a dual‐frame random‐digit‐dial (RDD) telephone survey in which samples are selected from landline and cell phone sampling frames. The estimators are subject to sampling and nonsampling errors. To reduce sampling variability when an opti...
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Published in | Statistics in medicine Vol. 38; no. 23; pp. 4718 - 4732 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
England
Wiley Subscription Services, Inc
15.10.2019
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Subjects | |
Online Access | Get full text |
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Summary: | We discuss alternative estimators of the population total given a dual‐frame random‐digit‐dial (RDD) telephone survey in which samples are selected from landline and cell phone sampling frames. The estimators are subject to sampling and nonsampling errors. To reduce sampling variability when an optimum balance of landline and cell phone samples is not feasible, we develop an application of shrinkage estimation. We demonstrate the implications for survey weighting of a differential nonresponse mechanism by telephone status. We illustrate these ideas using data from the National Immunization Survey‐Child, a large dual‐frame RDD telephone survey sponsored by the Centers for Disease Control and Prevention and conducted to measure the vaccination status of American children aged 19 to 35 months. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 0277-6715 1097-0258 1097-0258 |
DOI: | 10.1002/sim.8329 |